AI Governance for Trading Funds

Every AI trade intent.
Evaluated, enforced, traced.

BridgeOS sits between your AI agents and execution. It evaluates every trade intent against your risk policies in real time, enforces the decision before the order is placed, and records a complete audit trail — before anything reaches your OMS.

Book a 20-min call → Currently onboarding design partners.
Real-time
Pre-execution evaluation
100%
Decisions traced
Fail-closed
No data = no approval
Zero-strategy
We see intents, not models
The Problem

AI agents are making autonomous trading decisions.
Most funds have no way to govern them.

Algorithmic strategies and AI agents now generate trade intents faster than any human can review. When they go wrong — wrong model, wrong market regime, wrong risk assumption — they go wrong fast. The damage compounds before anyone intervenes.

The regulators are watching. LPs are asking questions. And most funds have no audit trail, no policy enforcement layer, and no way to explain what the model decided and why.

From agent intent to execution — fully governed.

01
Intent received
An AI agent, quant model, or trader submits a trade intent to BridgeOS via API.
02
Policy evaluation
BridgeOS evaluates the intent against your risk policies in real time. Deterministic engine — no black box.
03
Decision enforced
Every intent receives a verdict before execution.

ALLOW  DENY  ESCALATE
04
Full trace recorded
Every decision is logged with the full policy evaluation trace — auditable by compliance, explainable to LPs.
Capabilities

Built for institutional-grade governance.

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Real-time policy evaluation
Pre-execution evaluation on every trade intent. Machine-readable risk policies with JSON threshold checks. Fail-closed by design — if data is stale or unavailable, the intent is denied.
Complete audit trail
Every intent, every policy check, every verdict — recorded. Timestamped decision logs with the full evaluation trace, ready for regulatory review or LP reporting.
Deterministic replay
Replay any historical period with different policy configurations. See exactly how the governance layer would have behaved — before you deploy a policy change.
Your models never leave your environment
BridgeOS evaluates trade intents — not your strategies. Your models, signals, and logic stay inside your infrastructure. We see what your OMS would see: an order. Nothing more.

Every verdict is explained, not just recorded.

BridgeOS doesn't give you a yes/no black box. Every decision comes with the full evaluation trace — which policies ran, what thresholds were checked, and why the intent was allowed, denied, or escalated.

When your compliance officer asks "why did the agent do this?", the answer is already logged.

decision · 2025-01-15T09:42:11Z
intent_id int-9f3a2b
book equity-indices
instrument ES1 (S&P 500 Fut.)
side BUY
notional $2,400,000

policies_evaluated 7
policies_passed 7

verdict ALLOW

# notional within book limit (87% utilized)
# drawdown policy: within 3% threshold
# concentration: sector within limit
# model confidence: 0.82 > min 0.65
Who It's For

Built for quant funds deploying AI in production.

CTO / Head of Engineering
A governance API that integrates with your existing stack. We evaluate trade intents — not your models or signals. No black box — the policy engine is deterministic and fully inspectable.
Risk Officer
Policies you define are enforced before execution — not after. Real-time alerts, kill-switch capability, and a complete decision log. Fail-closed by design.
Compliance Officer
Every decision is traced. Every policy check is logged. Audit-ready output for CVM, regulators, and LP reporting — without manual reconstruction.
Deterministic, not probabilistic The risk engine evaluates policies against hard thresholds. No AI deciding what's safe.
Fail-closed safety If position data is unavailable or stale (>60s), BridgeOS rejects the intent. No partial decisions.
Zero-strategy exposure We evaluate trade intents — the output of your model, not the model itself. Your strategies, signals, and logic are never transmitted.
Stack-agnostic Integrates with existing PMS, OMS, and EMS systems. Not a replacement — a governance layer on top.